We propose to develop a mini-computer system for the automatic analysis of left ventriculography in a clinical cardiac catheterization laboratory setting. This system will be designed to 1) provide frame by frame quantitative volume measurements 2) analyze wall motion abnormalities and 3) generate new information about left ventricular function. We will utilize the substantial expertise of the Stanford Artificial Intelligence Laboratory (Martiner photos and robotics) for processing images of low signal to noise ratio. Similarly the Cardiology unit has had considerable success in developing computer techniques for processing of hemodynamic, electrocardiographic and angiographic data. The methods to be used for automatic margin detection include contrast enhancement, image subtraction, directional edge finding and static and dynamic modelling. Initial development will use a large scale PDP-10 computer; however, development of a dedicated clinically oriented system necessitates implementation on a PDP-11 mini-computer so that it can be utilized in many other laboratories. The techniques we develop for radiographic image processing will be oriented towards future application to the problem of automatic analysis of ultrasound and isotope images.